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Abstract Background The hippocampus, with its complex subfields, is linked to numerous neuropsychiatric traits. While most research has focused on its global structure or a few specific subfields, a comprehensive analysis of hippocampal substructures and their genetic correlations across a wide range of neuropsychiatric traits remains underexplored. Given the hippocampus’s high heritability, considering hippocampal and subfield volumes (HASV) as endophenotypes for neuropsychiatric conditions is essential. Methods We analyzed MRI-derived volumetric data of hippocampal and subfield structures from 41,525 UK Biobank participants. Genome-wide association studies (GWAS) on 24 HASV traits were conducted, followed by genetic correlation, overlap, and Mendelian randomization (MR) analyses with 10 common neuropsychiatric traits. Polygenic risk scores (PRS) based on HASV traits were also evaluated for predicting these traits. Results Our analysis identified 352 independent genetic variants surpassing a significance threshold of 2.1 × 10−9 within the 24 HASV traits, located across 93 chromosomal regions. Notably, the regions 12q14.3, 17q21.31, 12q24.22, 6q21, 9q33.1, 6q25.1, and 2q24.2 were found to influence multiple HASVs. Gene set analysis revealed enrichment of neural differentiation and signaling pathways, as well as protein binding and degradation. Of 240 HASV-neuropsychiatric trait pairs, 75 demonstrated significant genetic correlations (P

Abstract Genetic testing is crucial for precision cancer medicine. However, detecting multiple same-site insertions or deletions (indels) is challenging. Here, we introduce CoHIT (Cas12a-based One-for-all High-speed Isothermal Test), a one-pot CRISPR-based assay for indel detection. Leveraging an engineered AsCas12a protein variant with high mismatch tolerance and broad PAM scope, CoHIT can use a single crRNA to detect multiple NPM1 gene c.863_864 4-bp insertions in acute myeloid leukemia (AML). After optimizing multiple parameters, CoHIT achieves a detection limit of 0.01% and rapid results within 30 minutes, without wild-type cross-reactivity. It successfully identifies NPM1 mutations in 30 out of 108 AML patients and demonstrates potential in monitoring minimal residual disease (MRD) through continuous sample analysis from three patients. The CoHIT method is also competent for detecting indels of KIT, BRAF, and EGFR genes. Integration with lateral flow test strips and microfluidic chips highlights CoHIT’s adaptability and multiplexing capability, promising significant advancements in clinical cancer diagnostics.

Abstract Background Early detection of colorectal neoplasms can reduce the colorectal cancer (CRC) burden by timely intervention for high-risk individuals. However, effective risk prediction models are lacking for personalized CRC early screening in East Asian (EAS) population. We aimed to develop, validate, and optimize a comprehensive risk prediction model across all stages of the dynamic adenoma-carcinoma sequence in EAS population. Methods To develop precision risk-stratification and intervention strategies, we developed three trans-ancestry PRSs targeting colorectal neoplasms: (1) using 148 previously identified CRC risk loci (PRS148); (2) SNPs selection from large-scale meta-analysis data by clumping and thresholding (PRS183); (3) PRS-CSx, a Bayesian approach for genome-wide risk prediction (PRSGenomewide). Then, the performance of each PRS was assessed and validated in two independent cross-sectional screening sets, including 4600 patients with advanced colorectal neoplasm, 4495 patients with non-advanced adenoma, and 21,199 normal individuals from the ZJCRC (Zhejiang colorectal cancer set; EAS) and PLCO (the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; European, EUR) studies. The optimal PRS was further incorporated with lifestyle factors to stratify individual risk and ultimately tested in the PLCO and UK Biobank prospective cohorts, totaling 350,013 participants. Results Three trans-ancestry PRSs achieved moderately improved predictive performance in EAS compared to EUR populations. Remarkably, the PRSs effectively facilitated a thorough risk assessment across all stages of the dynamic adenoma-carcinoma sequence. Among these models, PRS183 demonstrated the optimal discriminatory ability in both EAS and EUR validation datasets, particularly for individuals at risk of colorectal neoplasms. Using two large-scale and independent prospective cohorts, we further confirmed a significant dose–response effect of PRS183 on incident colorectal neoplasms. Incorporating PRS183 with lifestyle factors into a comprehensive strategy improves risk stratification and discriminatory accuracy compared to using PRS or lifestyle factors separately. This comprehensive risk-stratified model shows potential in addressing missed diagnoses in screening tests (best NPV = 0.93), while moderately reducing unnecessary screening (best PPV = 0.32). Conclusions Our comprehensive risk-stratified model in population-based CRC screening trials represents a promising advancement in personalized risk assessment, facilitating tailored CRC screening in the EAS population. This approach enhances the transferability of PRSs across ancestries and thereby helps address health disparity. Graphical Abstract

Background: Depression and long non-coding RNA (lncRNA) have been reported to be associated with tumor progression and prognosis in gastric cancer (GC). This study aims to build a GC risk classification and prognosis model based on depression-related lncRNAs (DRLs). Methods: To develop a risk model, we performed univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses using RNA sequencing data of GC from The Cancer Genome Atlas (TCGA) and depression-related genes (DRGs) from previous studies. Kaplan-Meier analysis, receiver operating characteristic (ROC) curve analysis, nomogram construction, pathway enrichment analysis, assessment of immunological features, and drug sensitivity testing were conducted using a series of bioinformatics methods. Results: Seven DRLs were identified to build a prognostic model, whose robustness was verified in an internal cohort. Subsequent prognostic analyses found that high risk scores were associated with worse overall survival (OS). Univariate and multivariate analyses revealed that the risk score could be used as an independent prognostic factor. Furthermore, the ROC curve indicated that the risk score had higher diagnostic efficiency than traditional clinicopathological features. The calibration curve confirmed the accuracy and reliability of the nomogram. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that there were differences in digestive system and nervous system-related pathways between the high- and low-risk groups. Results of tumor mutational burden (TMB) and tumor immune dysfunction and exclusion (TIDE) analyses indicated that patients in the low-risk group had a better response rate to immunotherapy. Finally, the results of drug sensitivity analysis showed that risk score could influence sensitivity to EHT 1864 in GC. Conclusion: We have successfully developed and verified a 7-DRL risk model which can assess the prognosis and immunological features and guide individualized therapy of GC patients.

Hypoxia is the common characteristic of almost all solid tumors, which prevents therapeutic drugs from reaching the tumors. Therefore, the development of new targeted agents for the accurate diagnosis of hypoxia tumors is widely concerned. As carbonic anhydrase IX (CA IX) is abundantly distributed on the hypoxia tumor cells, it is considered as a potential tumor biomarker. 4-(2-Aminoethyl)benzenesulfonamide (ABS) as a CA IX inhibitor has inherent inhibitory activity and good targeting effect. In this study, Ag2S quantum dots (QDs) were used as the carrier to prepare a novel diagnostic and therapeutic bioprobe (Ag2S@polyethylene glycol (PEG)-ABS) through ligand exchange and amide condensation reaction. Ag2S@PEG-ABS can selectively target tumors by surface-modified ABS and achieve accurate tumor imaging by the near infrared-II (NIR-II) fluorescence characteristics of Ag2S QDs. PEG modification of Ag2S QDs greatly improves its water solubility and stability, and therefore achieves high photothermal stability and high photothermal conversion efficiency (PCE) of 45.17%. Under laser irradiation, Ag2S@PEG-ABS has powerful photothermal and inherent antitumor combinations on colon cancer cells (CT-26) in vitro. It also has been proved that Ag2S@PEG-ABS can realize the effective treatment of hypoxia tumors in vivo and show good biocompatibility. Therefore, it is a new efficient integrated platform for the diagnosis and treatment of hypoxia tumors.

Abstract. Background:. Findings on the association of genetic factors and colorectal cancer (CRC) survival are limited and inconsistent, and revealing the mechanism underlying their prognostic roles is of great importance. This study aimed to explore the relationship between functional genetic variations and the prognosis of CRC and further reveal the possible mechanism. Methods:. We first systematically performed expression quantitative trait locus (eQTL) analysis using The Cancer Genome Atlas (TCGA) dataset. Then, the Kaplan-Meier analysis was used to filter out the survival-related eQTL target genes of CRC patients in two public datasets (TCGA and GSE39582 dataset from the Gene Expression Omnibus database). The seven most potentially functional eQTL single nucleotide polymorphisms (SNPs) associated with six survival-related eQTL target genes were genotyped in 907 Chinese CRC patients with clinical prognosis data. The regulatory mechanism of the survival-related SNP was further confirmed by functional experiments. Results:. The rs71630754 regulating the expression of endoplasmic reticulum aminopeptidase 1 (ERAP1) was significantly associated with the prognosis of CRC (additive model, hazard ratio [HR]: 1.43, 95% confidence interval [CI]: 1.08-1.88, P = 0.012). The results of dual-luciferase reporter assay and electrophoretic mobility shift assay showed that the A allele of the rs71630754 could increase the binding of transcription factor 3 (TCF3) and subsequently reduce the expression of ERAP1. The results of bioinformatic analysis showed that lower expression of ERAP1 could affect the tumor immune microenvironment and was significantly associated with severe survival outcomes. Conclusion:. The rs71630754 could influence the prognosis of CRC patients by regulating the expression of the immune-related gene ERAP1. Trial Registration:. No. NCT00454519 (https://clinicaltrials.gov/)

Abstract The 3D crop data obtained during cultivation is of great significance to screening excellent varieties in modern breeding and improvement on crop yield. With the rapid development of deep learning, researchers have been making innovations in aspects of both data preparation and deep network design for segmenting plant organs from 3D data. Training of the deep learning network requires the input point cloud to have a fixed scale, which means all point clouds in the batch should have similar scale and contain the same number of points. A good down-sampling strategy can reduce the impact of noise and meanwhile preserve the most important 3D spatial structures. As far as we know, this work is the first comprehensive study of the relationship between multiple down-sampling strategies and the performances of popular networks for plant point clouds. Five down-sampling strategies (including FPS, RS, UVS, VFPS, and 3DEPS) are cross evaluated on five different segmentation networks (including PointNet + + , DGCNN, PlantNet, ASIS, and PSegNet). The overall experimental results show that currently there is no strict golden rule on fixing down-sampling strategy for a specific mainstream crop deep learning network, and the optimal down-sampling strategy may vary on different networks. However, some general experience for choosing an appropriate sampling method for a specific network can still be summarized from the qualitative and quantitative experiments. First, 3DEPS and UVS are easy to generate better results on semantic segmentation networks. Second, the voxel-based down-sampling strategies may be more suitable for complex dual-function networks. Third, at 4096-point resolution, 3DEPS usually has only a small margin compared with the best down-sampling strategy at most cases, which means 3DEPS may be the most stable strategy across all compared. This study not only helps to further improve the accuracy of point cloud deep learning networks for crop organ segmentation, but also gives clue to the alignment of down-sampling strategies and a specific network.

Abstract Genomic abnormalities are strongly associated with cancer and infertility. In this study, we develop a simple and efficient method — multiple genetic abnormality sequencing (MGA-Seq) — to simultaneously detect structural variation, copy number variation, single-nucleotide polymorphism, homogeneously staining regions, and extrachromosomal DNA (ecDNA) from a single tube. MGA-Seq directly sequences proximity-ligated genomic fragments, yielding a dataset with concurrent genome three-dimensional and whole-genome sequencing information, enabling approximate localization of genomic structural variations and facilitating breakpoint identification. Additionally, by utilizing MGA-Seq, we map focal amplification and oncogene coamplification, thus facilitating the exploration of ecDNA’s transcriptional regulatory function.

Abstract Background A novel CT-linac (kilovolt fan-beam CT-linac) has been introduced into total marrow and lymphoid irradiation (TMLI) treatment. Its integrated kilovolt fan-beam CT (kV FBCT) can be used not only for image guidance (IGRT) but also to re-calculate the dose. Purpose This study reported our clinical routine on performing TMIL treatment on the CT-linac, as well as dose distribution comparison between planned and re-calculated based on IGRT FBCT image sets. Methods 11 sets of data from 5 male and 6 female patients who had underwent the TMLI treatment with uRT-linac 506c were selected for this study. The planning target volumes consist of all skeletal bones exclusion of the mandible and lymphatic sanctuary sites. A planned dose of 10 Gy was prescribed to all skeletal bones exclusion of the mandible in two fractions and 12 Gy in two fractions was prescribed to lymphatic sanctuary sites. Each TMLI plan contained two sub-plans, one dynamic IMRT for the upper body and the other VMAT for the lower extremity. Two attempts were made to obtain homogeneous dose in the overlapping region, i.e., applying two plans with different isocenters for the treatment of two fractions, and using a dose gradient matching scheme. The CT scans, including planning CT and IGRT FBCT, were stitched to a whole body CT scan for dose distribution evaluation. Results The average beam-on time of Planupper is 30.6 min, ranging from 24.9 to 37.5 min, and the average beam-on time of Planlower is 6.3 min, ranging from 5.7 to 8.2 min. For the planned dose distribution, the 94.79% of the PTVbone is covered by the prescription dose of 10 Gy (V10), and the 94.68% of the PTVlymph is covered by the prescription dose of 12 Gy (V12). For the re-calculated dose distribution, the 92.17% of the PTVbone is covered by the prescription dose of 10 Gy (V10), and the 90.07% of the PTVlymph is covered by the prescription dose of 12 Gy (V12). The results showed that there is a significant difference (p 0.05) between planned dose and re-calculated dose on selected organs, except for right lens (p

Abstract Genome-wide association studies have identified numerous variants associated with human complex traits, most of which reside in the non-coding regions, but biological mechanisms remain unclear. However, assigning function to the non-coding elements is still challenging. Here we apply Activity-by-Contact (ABC) model to evaluate enhancer-gene regulation effect by integrating multi-omics data and identified 544,849 connections across 20 cancer types. ABC model outperforms previous approaches in linking regulatory variants to target genes. Furthermore, we identify over 30,000 enhancer-gene connections in colorectal cancer (CRC) tissues. By integrating large-scale population cohorts (23,813 cases and 29,973 controls) and multipronged functional assays, we demonstrate an ABC regulatory variant rs4810856 associated with CRC risk (Odds Ratio = 1.11, 95%CI = 1.05–1.16, P = 4.02 × 10−5) by acting as an allele-specific enhancer to distally facilitate PREX1, CSE1L and STAU1 expression, which synergistically activate p-AKT signaling. Our study provides comprehensive regulation maps and illuminates a single variant regulating multiple genes, providing insights into cancer etiology.

Standards play significant roles in the development of technology and economics, while the cooperation between drafters directly determines the quality of standard systems. The cooperation prediction is a significant while challenging problem for seeking new cooperation chances between drafting units due to their differences in experience and professional ability. In this study, an integrated artificial intelligence method is proposed for cooperation prediction using the link prediction method, text analysis, and network modeling. Specifically, we develop a multi-layer standard network formed by standard citation relationships and cooperation relationships between drafters. Then, a set of novel metrics is designed for predicting the cooperation between drafters considering the knowledge, experience, and professional capability. These metrics are further integrated into a neural network to improve the prediction accuracy. The priorities of our method in terms of prediction accuracy are verified with realistic data of Chinese environmental health standards. The prediction results provide strong support for the selection of drafters and further optimize the structure of standard systems.

Abstract Osteosarcoma (OS) is the most common bone malignancy and preferably occurs in children and adolescents. Despite significant advances in surgery and chemotherapy for OS over the past few years, overall survival rates of OS have reached a bottleneck. Thus, extensive researches aimed at developing new therapeutic targets for OS are urgently needed. Autophagy, a conserved process which allows cells to recycle altered or unused organelles and cellular components, has been proven to play a critical role in multiple biological processes in OS. In this article, we summarized the association between autophagy and proliferation, metastasis, chemotherapy, radiotherapy, and immunotherapy of OS, revealing that autophagy‐related genes and pathways could serve as potential targets for OS therapy.

Abstract Background Osteosarcoma (OS) is the most frequent cancer derived from bone, and the prognosis of OS is poor. Metabolic alterations have been previously reported to contribute to the development of OS, and arsenic compounds have been suggested to exhibit strong anti-OS effects. However, few studies have described the therapeutic efficiency of arsenic compounds by targeting metabolism in OS. Methods Here, we presented a novel organo-arsenic compound, Aa-Z2, and its antitumour efficacy against OS both in vitro and in vivo. Results Aa-Z2 induced OS cell apoptosis, G2/M phase arrest, and autophagy through the accumulation of reactive oxygen species (ROS). Elevated ROS functioned by promoting the mitochondrial-dependent caspase cascade and attenuating the PI3K/Akt/mTOR signalling pathway. N-acetylcysteine (NAC), a kind of ROS scavenger, could reverse the effects of Aa-Z2 treatment on 143B and HOS cells. Specifically, by targeting pyruvate dehydrogenase kinase 1 (PDK-1), Aa-Z2 induced changes in mitochondrial membrane potential and alterations in glucose metabolism to accumulate ROS. Overexpression of PDK-1 could partially desensitize OS cells to Aa-Z2 treatment. Importantly, Aa-Z2 suppressed tumour growth in our xenograft osteosarcoma model. Conclusion The study provides new insights into the mechanism of Aa-Z2-related metabolic alterations in OS inhibition, as well as pharmacologic evidence supporting the development of metabolism-targeting therapeutics.

Abstract Background Osteosarcoma is the most frequent primary bone malignancy with a poor prognosis because of pulmonary metastasis. Autophagy is strongly associated with tumor metastasis, and it is valuable to construct an autophagy-related gene risk model for predicting the prognosis of osteosarcoma. Methods We obtained ARGs from the Human Autophagy Database and RNA-sequencing data of osteosarcoma patients from the Gene Expression Omnibus (GEO) database. Subsequently, univariate and multivariate cox regression analyses were performed to construct a three-gene prognostic model and its accuracy was further confirmed in the Therapeutic Applications Research to Generate Effective Treatments (TARGET) database. Afterward, we detected the expression levels and effects on osteosarcoma cells metastasis of MYC and MBTPS2, which were involved in the model. Results In both training and verification cohorts, patients with lower risk scores had longer OS, and the model was identified as an independent prognostic factor in osteosarcoma. Besides, the ROC curve demonstrated the reliability of the model. Furthermore, RT-qPCR, Western Blotting and IHC results indicated that MYC and MBTPS2 were differently expressed in osteosarcoma tissues and cell lines. MYC knockdown or MBTPS2 overexpression prevented the capacity of migration and invasion in osteosarcoma cell lines through inhibiting cellular autophagy. Conclusion The risk model based on three ARGs had a strong ability to predict the prognosis of osteosarcoma patients. Our findings also suggested that MYC and MBTPS2 were two major factors regulating autophagy in osteosarcoma, and could serve as potential therapeutic targets for osteosarcoma.

This paper focuses on the long time dynamics for a class stochastic SEI model with standard incidence and infectivity in incubation period. Firstly, we investigate a unique global positive solution almost surely for any positive initial value. Secondly, we obtain a unique stationary measure and the extinction condition of the epidemic based on the technique of Lyapunov function and inequalities. Thirdly, we explore the asymptotic behavior of the solutions around equilibriums of the corresponding deterministic model from different aspects. Finally, we establish some numerical simulations to illustrate the main presented results.

This paper reveals dynamical behaviors in the stochastic multimolecule oscillatory reaction model with Poisson jumps. First, this system is proved to have a unique global positive solution via the Lyapunov technique. Second, the existence and uniqueness of general random attractors for its stochastic homeomorphism flow is proved by the comparison theorem, and meanwhile, a criterion for the existence of singleton sets is obtained. Finally, numerical simulations are used to illustrate the predicted random attractors.

Advances in the understanding of psychoneuroimmunology in the past decade have emphasized the notion that stress and cancer are interlinked closely. Durable chronic stress accelerated tumorigenesis and progression, which is unfavorable for clinical outcomes of cancer patients. Available evidence has provided unprecedented knowledge about the role and mechanisms of chronic stress in carcinogenesis, the most well-known one is dysfunction of the hypothalamus-pituitary-adrenal (HPA) axis and the sympathetic nervous system (SNS). With abnormal activation of neuroendocrine system, stress-related hormones contribute to increased oncogenes expression, exacerbated chronic inflammation and impaired immunologic function. In addition, accumulating studies have demonstrated that diverse stress interventions including pharmacological approaches, physical exercises and psychological relaxation have been administered to assist in mental disorders reduction and life quality improvement in cancer patients. In this review, we systematically summarize the connection and mechanisms in the stress-immune-cancer axis identified by animal and clinical studies, as well as conclude the effectiveness and deficiencies of existing stress management strategies.

Abstract Recently, a diagnostic helical CT is integrated into a linear accelerator, called uRT-linac 506c, whose CT scanning dataset can be directly used to do simulation. This novel structure provides a possibility for online adaptive radiotherapy. For adaptive radiotherapy, the carbon fiber couch is an essential external device for supporting and positioning patients. And the effect on dose attenuation and distribution caused by a couch is inevitable and vital for precise treatment. In this research, the couch equipped with uRT-linac 506c was evaluated on the radiation dosimetry effect. The treatment couch equipped on the uRT-linac 506c accelerator was evaluated, and its effect on the attenuation, surface dose and dose buildup were measured for different phantom positions (offset = 0 cm, offset = + 10 cm and offset = − 10 cm, respectively) and different gantry angles. Since uRT-linac 506c is exclusively capable to provide diagnostic CT scanning data with real relative electron density (RED), this CT scanning data of the couch can be used directly in uRT-TPS to design plans. This scanned couch dataset was designated as the model A. The model B was a dummy structure of a treatment couch inserted with artificially preset RED. The dose calculation accuracy of these two models was compared using PB, CC, and MC on uRT-TPS. With the effect of carbon fiber couch, the surface dose was increased at least 97.94% for 25 × 25 cm2 field and 188.83% for 10 × 10 cm2 field, compared with those without. At different phantom positions (offset = 0, + 10, − 10 cm), the attenuation for 6 MV photon beam at gantry angle 180° were 4.4%, 4.4%, and 4.3%, respectively, and varied with changes of gantry angle. There do exists dose deviation between measurement and TPS calculation with the involvement of treatment couch, among the three algorithms, MC presented the least deviation, and the model A made less and steadier deviation than the model B, showing promising superiority. The attenuation, surface dose, and buildup effects of the carbon fiber couch in this study were measured similarly to most counterparts. The dose deviation calculated based on the couch dataset scanned by the diagnostic helical CT was smaller than those based on a dummy couch. This result suggests that an accelerator equipped with a diagnostic CT, which can help reduce the dose deviation of the carbon fiber couch, is a promising platform for online adaptive radiotherapy.

Abstract This study was designed to investigate the prognostic value of the number and sites of extracranial metastasis (ECM) in NSCLC patients with BM. NSCLC patients with BM from the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015 were enrolled in analysis. Patients from 2010 to 2013 were included in the training set and those from 2014 to 2015 in the validation set. ECM sites among different subtypes of NSCLC were compared by Chi‐square tests. Kaplan–Meier methods and Cox regression models were performed to analyze survival data. Competing‐risks analysis was used to predict cumulative incidence rates for CSS and non‐CSS cause. We included 5974 patients in the training cohort and 3561 patients in the validation cohort. Most (nearly 80%) NSCLC patients with BM showed 0–1 involved extracranial organ, with the most and least common ECM organ being bone and distant lymph nodes (DLNs) among all subtypes of NSCLC, respectively. The number of involved extracranial organs was an independent prognostic factor for patients with BM from NSCLC (p

Background: Tumor mutational burden (TMB) is a genomic biomarker that can predict favorable responses to immune checkpoint inhibitors (ICIs). Although we have better understanding of TMB in cancer immunity and cancer immunotherapy, the relationship between TMB and the clinical efficacy of ICIs remains unknown in the treatment of melanoma patients. Here, we conduct a systematic review and meta-analysis to evaluate the predictive value of TMB on the efficacy of ICIs in patients with melanoma.Methods: We systematically collected data from PubMed, Embase, Cochrane Library, CNKI, China Biomedical Database (CBM), and Wanfang Database. The end date was set to 26 June 2021. We included retrospective studies or clinical trials of ICIs that reported hazard ratios (HRs) for overall survival and/or progression-free survival according to TMB. Data for 1,493 patients from 15 studies were included. In addition, pooled effect size, heterogeneity analysis, sensitivity analysis, publication bias detection, and subgroup analysis were performed based on the included data.Results: Patients with high TMB showed significantly improved OS (HR = 0.49, 95% CI: 0.33, 0.73; p = 0.001) and PFS (HR = 0.47, 95% CI: 0.33, 0.68; p < 0.001) compared with patients with low TMB. This association was very good in patients treated with monotherapy, that is, anti-CTLA-4 or anti-PD-(L)-1 inhibitors, but not for the patients treated with a combination of the two drugs. The subgroup analysis results showed that heterogeneity was substantial in the targeted next-generation sequencing (NGS) group. Publication bias was detected, and the results were visualized using the funnel chart. And sensitivity analysis and trim-and-fill method analysis showed that our results were stable and reliable.Conclusion: High TMB is associated with improved OS and PFS in melanoma patients treated with mono-drug ICIs. TMB determined by NGS should be standardized to eliminate heterogeneity. Therefore, the role of TMB in identifying melanoma patients who may benefit from ICI should be further determined in more randomized controlled trials in the future.

The automated valuation of benchmark land price plays an essential role in regulating land demand in Chinese real-estate market as the big data are currently accumulated rapidly. However, this problem becomes highly challenging due to the multidimension, large volume, and nonlinearity of the land price-influencing factors. In this paper, an effective data-driven automated valuation framework is proposed for valuing real estate assets by combining a GIS (geographic information system) and neural network technologies. This framework can automatically obtain the values of spatial factors affecting land price from GIS and generate training set data for training the neural network to identify the complex relationship between all kinds of factors and benchmark land prices. The effectiveness and universality of the framework is verified via the data of benchmark land prices in Wuhan. The framework can be applied for automated benchmark land price valuation in other cities.

With the development of Internet technology, e-commerce platforms have emerged one after another, and the competition of the fruit e-commerce market is increasingly intensified. How to boost customer demand by improving their purchase intention has become a key issue. The study identified the critical conditions leading to high purchase intention of fruits through fuzzy-set qualitative comparative analysis. The empirical analysis was conducted based on an online questionnaire of 344 Internet users. The results reveal that high purchase intention comes from high fruit quality, high fruit price concessions and supply service, and low perceived risk (peripheral conditions). In addition, high purchase intention can also be realized from high fruit quality, high fruit price concessions, high supply service, and high website information quality (peripheral conditions). This study provides more nuanced thinking of how to improve online purchase intention of fruits.

ObjectiveTo investigate the impact of the human papillomavirus (HPV) status on head and neck squamous cell carcinoma (HNSCC) arising from different anatomic subsites.MethodsHNSCC patients with known HPV status from the Surveillance, Epidemiology, and End Results (SEER) database between 2010–2015 were included in our analysis. Patients were classified into three categories of HNSCC according to Site recode ICD-O-3/WHO 2008 and Primary Site-labeled, namely, oropharynx, hypopharynx, and nasopharynx. Logistic regression model was conducted to evaluate the relationship between patient characteristics and HPV status. Kaplan-Meier methods and COX regression analysis were used to analyze survival data.ResultsA total of 9,943 HNSCC patients with known HPV status from the SEER database were enrolled, with 6,829 (68.7%) HPV-positive patients. HPV-positive and HPV-negative HNSCC were distinct and had different clinical and socioeconomic features (all P < 0.001). Primary sites, socioeconomical factors (age, sex, marital status, and race), and pathological features (TNM stage and grade) were closely related with HPV status (all P < 0.001). HPV-positive status was a favorable prognostic marker in HNSCC patients with cancers of the oropharynx and hypopharynx (all P < 0.001), but was not in nasopharyngeal carcinoma patients (P = 0.843). A total of 8,933 oropharyngeal carcinoma (OPC) and 558 hypopharyngeal carcinoma (HPC) patients were divided into the training and validation cohorts with a ratio of 1:1. Significant prognostic factors of the OS yielded by multivariate COX analysis in the training cohort were integrated to construct nomograms for OPC and HPC patients. The prognostic models showed a good discrimination with a C-index of 0.79 ± 0.007 and 0.73 ± 0.023 in OPC and HPC, respectively. Favorable calibration was reflected by the calibration curves. Additionally, corresponding risk classification systems for OPC and HPC patients based on the nomograms were built and could perfectly classify patients into low-risk, intermediated-risk, high-risk groups. OS in the three risk groups was accurately differentiated and showed a good discrimination.ConclusionHPV positivity was associated with an improved survival in HNSCC patients with cancers of the oropharynx and hypopharynx. Nomograms and corresponding risk classification systems were constructed to assist clinicians in evaluating the survival of OPC and HPC patients.

Primary central nervous system lymphoma (PCNSL) is a rare subtype of extra-nodal lymphoma. The high relapse rate of PCNSL remains a major challenge to the hematologists, even though patients exhibit high sensitivity to the methotrexate-based chemotherapeutic regimens. Recently, the advent of Bruton’s tyrosine kinase inhibitor (BTKi) and CAR T treatment has made more treatment options available to a proportion of patients. However, whether BTKi monotherapy should be given alone or in combination with conventional chemotherapy is still a clinical question. The status of CAR T therapy for PCNSLs also needs to be elucidated. In this review, we summarized the latest progress on the epidemiology, pathology, clinical manifestation, diagnosis, and treatment options for PCNSLs.

The existing studies have indicated that abusive supervision affects creativity; however, the specific impact mechanism is still unclear due to the uncertain relationship between leadership and employee creativity. Based on the resource perspective, this study examines the influence of abusive supervision on creativity through psychological availability (PA) and the moderating of this mediation by performance improvement attribution (PIA). Based on a survey of 234 employees', the hypotheses have been tested and the results reveal that abusive supervision had a detrimental effect on employee creativity partially mediated by employee PA, and employees' PIA moderated the mediation. This study offers new insights into the mechanisms associated with the relationship between abusive supervision and creativity.

In standardization, the selection of the most influential institutions in drafting standards of specific areas is essential for improving the structure of industrial standard system. However, this problem becomes highly complex due to the large number of drafters and their influences are difficult to measure. This paper presents a research framework for assessing the importance of drafters in standardization based on a two-layer network model formed by the citation relationship between standards and the co-authorship relationship between drafters. Firstly, multiple structural indicators are integrated by the AHP to evaluate the importance of standards. Secondly, the importance of drafters are assessed by designing multidimensional indicators and verified through the case study of China's mobile communication industry. The results show that our indicators can reflect the industrial leadership gained by the participation of standards-drafting. Finally, managerial recommendations are proposed for drafting standards.

Exploring the characteristics of safety risks is crucial for deeply understanding and promoting traffic construction safety. Bridge and tunnel construction engineering is of high risk, which has been studied separately, while mega traffic engineering projects often combine them, leading to increased complexity. In this study, a research framework is proposed to explore the risk characteristics of bridge-tunnel hybrid construction engineering, which can be applied in other types of hybrid constructions. The real data with respect to 67 typical bridge and 64 tunnel accidents was collected from the database of a large traffic construction enterprise in China. 146 risk factors and 326 trigger relations are extracted to establish bridge and tunnel construction risk subnetworks. Moreover, a whole risk network is established by combing the two subnetworks together,. With the network scale, diameter, and other metrics, the properties of the risk networks are revealed. The critical risk factors in the construction of bridges and tunnels are identified. The results show that most of the accidents are attributed to management and worker factors, while purely environmental factors do not significantly contribute to the occurrence of the accidents. The results provide some prevention and post-remedy safety suggestions for the management of bridge and tunnel construction.

A standard system, which is a powerful tool in maintaining the normal operations and development of a specific industry, is intrinsically a complex network composed of numerous standards which coordinate and interact with each other. In a networked standard system, the identification of critical standards is of great significance when drafting and revising standards. However, a majority of the existing literature has focused on the citation relationships between standards while ignoring the intrinsic interdependent relationships between the contents of standards. To overcome this limitation, we utilize the text similarity approach (TSA) to quantify the relationship intensity between each pair of standards, in order to generate a directed weighted network. The critical contribution of this study is that the similarity computed by the TSA is incorporated into the traditional PageRank algorithm for the identification of critical standards. The improved algorithm comprehensively considers the quantity and importance of neighboring standards and the citation intensity, as quantified by TSA. The algorithm is finally validated using the Chinese environmental health standards through comparison with the traditional PageRank algorithm and different classic measurements.

Blood cell analysis is essential for the diagnosis and identification of hematological malignancies. The use of digital microscopy systems has been extended in clinical laboratories. Super-resolution microscopy (SRM) has attracted wide attention in the medical field due to its nanoscale spatial resolution and high sensitivity. It is considered to be a potential method of blood cell analysis that may have more advantages than traditional approaches such as conventional optical microscopy and hematology analyzers in certain examination projects. In this review, we firstly summarize several common blood cell analysis technologies in the clinic, and analyze the advantages and disadvantages of these technologies. Then, we focus on the basic principles and characteristics of three representative SRM techniques, as well as the latest advances in these techniques for blood cell analysis. Finally, we discuss the developmental trend and possible research directions of SRM, and provide some discussions on further development of technologies for blood cell analysis.

The COVID-19 outbreak caused by SARS-CoV-2 challenges the medical system by interfering with routine therapies for many patients with chronic diseases. In patients with cancer receiving immune checkpoint inhibitors (ICIs), difficulties also arise from the incomplete understanding of the intricate interplay between their routine treatment and pathogenesis of the novel virus. By referring to previous ICI-based investigations, we speculate that ICIs themselves are not linked to high-infection risks of respiratory diseases or inflammation-related adverse effects in patients with cancer. Moreover, ICI treatment may even enhance coronavirus clearance in some patients with malignant tumor by boosting antiviral T-cell responsiveness. However, the ‘explosive’ inflammation during COVID-19 in some ICI-treated patients with cancer was illustrated as exuberant immunopathological damage or even death. In case of the COVID-19 immunopathogenesis fueled by ICIs, we propose a regular monitor of pathogenic T-cell subsets and their exhaustion marker expression (eg, Th17 and interleukin (IL)-6-producing Th1 subsets with surface programmed death 1 expression) to guide the usage of ICI. Here we aimed to address these considerations, based on available literature and experience from our practice, that may assist with the decision-making of ICI administration during the pandemic.

Background: Asymptomatic carriers were positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) without developing symptoms, which might be a potential source of infection outbreak. Here, we aim to clarify the epidemiologic and influencing factors of asymptomatic carriers in the general population. Methods: In our hospital, all hospital staff have received throat swab RT-PCR test, plasma COVID-19 IgM/IgG antibodies test and chest CT examination. We analyzed the correlation between infection rates and gender, age, job position, work place and COVID-19 knowledge training of the staff. After that, all asymptomatic staff were re-examined weekly for 3 weeks. Findings: A total of 3764 hospital staff were included in this single-center cross-sectional study. Among them, 126 hospital staff had abnormal findings, and the proportion of asymptomatic infection accounted for 0.76% (28/3674). There were 26 staff with IgM+, 73 with IgG+, and 40 with ground glass shadow of chest CT. Of all staff with abnormal findings, the older they are, the more likely they are to be the staff with abnormal results, regardless of their gender. Of 3674 hospital staff, the positive rate of labor staff is obviously higher than that of health care workers (HCWs) and administrative staff (P0.05). The positive rate of HCWs who participated in the COVID-19 knowledge training was lower than those did not participate in early training (P 0.05). During 3 weeks follow-up, all asymptomatic patients did not present the development of clinical symptoms or radiographic abnormalities after active intervention in isolation point. Interpretation: To ensure the safety of resumption of work, institutions should conduct COVID-19 prevention training for staff and screening for asymptomatic patients, and take quarantine measures as soon as possible in areas with high density of population. Funding: The Key Project for Anti-2019 novel Coronavirus Pneumonia from the Ministry of Science and Technology, China; Wuhan Emergency Technology Project of COVID-19 epidemic, China.

Abnormal coagulation parameters and potential benefits of anticoagulant therapy in general population with novel coronavirus pneumonia (COVID-19) have been reported. However, limited data are available on cancer patients. Coagulation indexes and inflammation parameters in 57 cancer patients with SARS-CoV-2 infection with different severity were retrospectively analyzed. We found that D-dimer levels were increased in 33 patients (57.9%, median: 790 ng/mL). Compared with ordinary type patients, severe and critical ill patients had decreased MPV values (P = 0.006), prolonged PT (median: 13.3 vs. 11.5 vs. 11.4 s, P < 0.001), significant higher D-dimer levels (median: 2,400 vs. 940 vs. 280 ng/mL, P < 0.001), higher PCT levels (median: 0.17 vs. 0.055 vs. 0.045 ng/mL, P = 0.002), higher IL-6 (median: 20.6 vs. 2.3 vs. 3.0 pg/mL, P = 0.040), and decreased PaO2 (median: 68 vs. 84 vs. 96 mm Hg, P < 0.001). Importantly, three patients, one severe and two critical ill type, with increased D-dimer survived after anticoagulant therapy with continuous heparin infusion. Increased D-dimer levels positively correlated with increased PCT levels (r = 0.456, P = 0.002) and IL-6 levels (r = 0.501, P = 0.045). A negative correlation between D-dimer levels and PaO2 levels (r = −0.654, P = 0.021) were also existed. Cancer patients with COVID-19 showed prominent hypercoagulability associated with severe inflammation, anticoagulation therapy might be useful to improve the prognosis and should be immediately used after the onset of hypercoagulability.

Background: Coronavirus disease 2019 (COVID-19) has been widely spread and caused tens of thousands of deaths, especially in patients with severe COVID-19. This analysis aimed to explore risk factors for mortality of severe COVID-19, and establish a scoring system to predict in-hospital deaths. Methods: Patients with COVID-19 were retrospectively analyzed and clinical characteristics were compared. LASSO regression as well as multivariable analysis were used to screen variables and establish prediction model. Findings: A total of 2529 patients with COVID-19 was retrospectively analyzed, and 452 eligible severe COVID-19 were used for finally analysis. In training cohort, the median age was 66•0 years while it was 73•0 years in non-survivors. Patients aged 60–75 years accounted for the largest proportion of infected populations and mortality toll. Anti-SARS-CoV-2 antibodies were monitored up to 54 days, and IgG levels reached the highest during 20–30 days. No differences were observed of antibody levels between severe and non-severe patients. About 60.2% of severe patients had complications. Among acute myocardial injury (AMI), acute kidney injury (AKI) and acute liver injury (ALI), the heart was the earliest injured organ, whereas the time from AKI to death was the shortest. Age, diabetes, coronary heart disease (CHD), percentage of lymphocytes (LYM%), procalcitonin (PCT), serum urea, C reactive protein and D-dimer (DD), were identified associated with mortality by LASSO binary logistic regression. Then multivariable analysis was performed to conclude that old age, CHD, LYM%, PCT and DD remained independent risk factors for mortality. Based on the above variables, a scoring system of COVID-19 (CSS) was established to divide patients into low-risk and high-risk groups. This model displayed good discrimination (AUC=0·919) and calibration (P=0·264). Complications in low-risk and high-risk groups were significantly different (P

MicroRNAs (miRNAs) can participate in many behaviors of various tumors. Prior studies have reported that miR-15b-5p in different tumors can either promote or inhibit tumor progression. In breast cancer, the role of miR-15b-5p is unclear. The main objective of this paper is to explore miR-15b-5p effects and their mechanisms in breast cancer using both in vitro and in vivo experiments. This study showed that miR-15b-5p expression was upregulated in breast cancer compared with normal breast tissue and was positively correlated with poor overall survival in patients. Knockdown of miR-15b-5p in MCF-7 and MD-MBA-231 breast cancer cells restrained cell growth and invasiveness and induced apoptosis, whereas overexpression of miR-15b-5p achieved the opposite effects. We next revealed a negative correlation between miR-15b-5p and heparanase-2 (HPSE2) expression in breast cancer. Knockdown of miR-15b-5p significantly increased HPSE2 expression at both mRNA and protein levels in breast cancer cells in vitro. The underlying mechanisms of miR-15-5p in breast cancer were investigated using luciferase activity reporter assay and rescue experiments. In addition, miR-15b-5p knockdown significantly inhibited tumor growth in a xenograft model in mice. In summary, we showed that miR-15b-5p promotes breast cancer cell proliferation, migration, and invasion by directly targeting HPSE2. Accordingly, miR-15b-5p may serve both as a tool for prognosis and as a target for therapy of breast cancer patients.

Competing to set industry standards is a strategic option to a variety of industries. This paper aims to investigate the role of standard drafting in the evolution of enterprises’ competitiveness in multiplex networks of standards. Specifically, network-based measurements are deliberately designed to evaluate the enterprises participation, contribution, and collaboration in drafting standards. By demonstrating the development of the standard system in China’s communication industry, the effectiveness of our measurement system is verified. Accompanied by empirical observation, the data analysis shows that the relevant governmental agencies dominate the whole standard system; basic-technology providers acquire greater competitiveness through participating in the standards drafting than the other kinds of enterprises. Finally, the corresponding managerial suggestions are offered.

Abstract Background The increase in the levels of reactive oxygen species (ROS) in acute myeloid leukemia (AML) patients has been previously described; thus, it is important to regulate ROS levels in AML. Methods Flow cytometry were used to assess the in vitro effect of compound kushen injection (CKI). Quantitative proteomics were used to analyse the mechanism. The AML patient-derived xenograft (PDX) model were used to evaluate the in vivo effect of CKI. Results We found that intracellular ROS levels in AML cells were decreased, the antioxidant capacity were increased when treated with CKI. CKI inhibited the proliferation of AML cells and enhanced the cytotoxicity of AML cells, which has few toxic effects on haematopoietic stem cells (HSCs) and T cells. At the single-cell level, individual AML cells died gradually by CKI treatment on optofluidic chips. CKI promoted apoptosis and arrested cell cycle at G1/G0 phase in U937 cells. Furthermore, higher peroxiredoxin-3 (Prdx3) expression levels were identified in CKI-treated U937 cells through quantitative proteomics detection. Mechanically, the expression of Prdx3 and peroxiredoxin-2 (Prdx2) was up-regulated in CKI-treated AML cells, while thioredoxin 1 (Trx1) was reduced. Laser confocal microscopy showed that the proteins Prdx2 could be Interacted with Trx1 by CKI treatment. In vivo, the survival was longer and the disease was partially alleviated by decreased CD45+ immunophenotyping in peripheral blood in the CKI-treated group in the AML PDX model. Conclusions Antioxidant CKI possess better clinical application against AML through the Prdxs/ROS/Trx1 signalling pathway.

Background/Aims: MicroRNAs (miRNAs) regulate the expressions of cancer-related genes, and are involved in the development and progression of various human cancers. Here, we performed further analyses to determine whether let-7d is functionally linked to Jab1 in breast cancer. Methods: In situ hybridization and immunohistochemical analyses were used to determine the level of let-7d and Jab1 in breast cancer clinical specimens and its correlation with clinicopathological data. Let-7d overexpressing breast cancer cell lines combined with mouse models bearing cell-derived xenografts were used to assess the functional role of let-7d both in vitro and in vivo. Results: In this study, we found that let-7d was downregulated in breast cancer tissues, coupled with the elevations of Jab1 protein expressions, compared with paired adjacent noncancerous breast tissues. Let-7d overexpression significantly suppressed the proliferation and invasion in MCF-7 and MDA-MB-231 cells. Dual luciferase reporter assay indicated that Jab1 was the direct target of let-7d. Stepwise studies from in vitro and in vivo experiments indicated that let-7d overexpression inhibited cell growth and decreased Jab1 expressions in breast cancer cells and nude mice tumor tissues. Statistical analyses demonstrated that breast cancer patients with low levels of let-7d or high levels of Jab1 had a significant correlation with worse prognosis. Conclusion: These findings provide novel insights into molecular mechanism of let-7d and Jab1 in tumor development and progression of breast cancer, and thus let-7d/Jab1 are novel potential therapeutic targets for breast cancer patients.

Acute myeloid leukemia (AML) is a common type of hematological malignancy that can progress rapidly. AML has a poor prognosis and a high incidence of relapse due to therapeutic resistance. Azelaic acid (AZA), a small molecular compound is known to exhibit antitumor effect on various tumor cells. This study aimed to evaluate the antiproliferative and immunoregulatory effects of AZA against AMLviathe activation of the notch signaling pathway. We found that AZA can inhibit the proliferation of AML cells. In addition, laser confocal microscopy showed AZA-treated AML cells began to swelling and undergo cytoplasmic vacuolization. Importantly, AZA promoted the proliferation of NK and T cells and increased the secretion of TNF-αand IFN-γ. AZA also increased the expression levels of CD107a and TRAIL in NK cells, and CD25 and CD69 in T cells to influence their activation and cytotoxic ability. AZA-treated NK cells can kill AML cells more efficiently at the single-cell level as observed under the microfluidic chips. Further mechanistic analysis using protein mass spectrometry analysis and Notch signaling reporter assay demonstrated that Notch1and Notch2 were up-regulated and the Notch signaling pathway was activated. Moreover, combining AZA with the Notch inhibitor, RO4929097, decreased the expression of Notch1and Notch2, and downstream HES1 and HEY1, which rendered AML cells insensitive to AZA-induced apoptosis and alleviated AZA-mediated cytotoxicity in AML. In vivo, AZA relieved the leukemic spleen infiltration and extended the survival. The percentage of CD3-CD56+NK cells and CD4+CD8+T cells as well as the secretion of cytotoxic cytokines was increased after the treatment of AZA. The overall findings reveal that AZA is a potential Notch agonist against AML in activating the Notch signaling pathway.

Longnoncoding RNAs (lncRNAs) are significantly correlated with cancer pathogenesis, development, and metastasis. Microarray analysis showed that lncRNA MRPS30-DT is overexpressed in breast carcinoma; however, the function of MRPS30-DT in breast cancer tumorigenesis remains unclear. In situ hybridization and immunohistochemical analysis were used to evaluate the expression levels of MRPS30-DT and Jab1 in clinical samples of breast carcinoma and their relation to survival outcome. qRT-PCR was used to measure MRPS30-DT and Jab1 mRNA expressions. Protein levels were detected using Western blot. Cell proliferation and invasion ability were evaluated via 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), colony formation, and transwell assays. MRPS30-DT was knocked down in breast cancer cells to investigate its potential functional roles in cell growth and metastasis in vitro and in vivo. We found that MRPS30-DT was upregulated in breast cancer specimens and was accompanied by high Jab1 expression compared with that of paired para-carcinoma tissues. Knocking down MRPS30-DT significantly inhibited cancer cell proliferation and invasion and induced apoptosis in breast cancer cells. Similarly, knocking down MRPS30-DT in MDA-MB-231 cells significantly suppressed tumor growth. Furthermore, knocking down MRPS30-DT markedly reduced Jab1 expression in breast cancer cells and murine carcinoma. Statistical analyses suggested that high MRPS30-DT or Jab1 levels in breast cancer patients were positively correlated with poor prognoses. These data indicate the possible mechanisms of MRPS30-DT and Jab1 in breast cancer; thus, MRPS30-DT and Jab1 may be novel prognostic biomarkers and potential therapeutic targets for breast cancer treatment.

Gastric cancer (GC) is one of the most common cancers, with a high incidence of cancer death. Despite various therapeutic approaches, the cures and prognosis of advanced GC remain poor. Natural killer (NK) cells, which are known as important lymphocytes in innate immunity, play vital roles in suppressing GC initiation, progression, and metastases. A wide range of clinical settings shows that increasing the number of NK cells or improving NK cell antitumor activity is promising in GC patients. NK cell adoptive therapy (especially expanded NK cells) is a safe and well-tolerated method, which can enhance NK cell cytotoxicity against GC. Meanwhile, cytokines, immunomodulatory drugs, immune checkpoint blockades, antibodies, vaccines, and gene therapy have been found to directly or indirectly activate NK cells to improve their killing activity toward GC. In this review, we summarize recent advancements in the relationship between NK cells and GC and point out all the innovative strategies that can enhance NK cells' function to inhibit the growth of GC.

A problem-specific routing algorithm integrating ant colony optimization (ACO) and integer-coded genetic algorithm (GA) is developed to address the newly observed limitations imposed by ultranarrow aisles and access restriction, which exist in the largest e-commerce enterprise with self-run logistics in China. Those limitations prohibit pickers from walking through the whole aisle, and the access restriction even allows them to access the pick aisles only from specific entrances. The ant colony optimization is mainly responsible for generating the initial chromosomes for the genetic algorithm, which then searches the near-optimal solutions of picker-routing with our novel chromosome design by recording the detailed information of access modes and subaisles. To demonstrate the merits of the proposed algorithm, a comprehensive simulation for comparison is conducted with 12 warehouse layouts with real order information. The simulation results show that the proposed hybrid algorithm is superior to dedicated heuristics in terms of solution quality. The impacts of the parameters with respect to warehouse layout on the picking efficiency are analyzed as well. Setting more connect aisles and cross aisles is suggested to effectively optimize the picking-service efficiency in the presence of access limitations.

Over recent years, online purchase platforms of fruits are increasingly emerged to advance the e-commerce development and improve quality of human life. Unfortunately, we empirically observed that a lot of enterprises selling fruits online have suffered from bankruptcy due to a lot of complicated factors, such as inefficient logistics, low acceptance of online platforms, and financial risks. One of the root causes responsible for such an unanticipated phenomenon is related to the purchase intention, which motivates us to investigate what are the dominant factors affecting the online purchase intention of fruits. The results can be of great significance to the development of fruit e-commerce enterprises in online marketing. Based on the technology acceptance model (TAM) and perceived risk theory (PRT), this research developed an integrated theoretical model to explore the influential factors underlying consumers' intention to purchase fruits online. A web-based survey of 344 consumers with ages below 30 was used to test the hypotheses in our theoretical model. Through sample collection with questionnaires, a structural equation model is developed to compute the coupling relationship between influential factors and purchase intention. The results reveal that fruit quality and price are dominantly affecting the willingness of consumers to purchase fruit. Surprisingly, we found that e-commerce platforms, information quality, and perceived risk are less significant. Finally, some specific suggestions are recommended for fruit e-commerce enterprises in devising effective marketing strategies.

This paper presents some analytical results on production and order dynamics in the context of a discrete-time VMI supply chain system composed of one retailer and one manufacturer. We firstly derive the lower bound and upper bound on the range of inventory fluctuations for the retailer under unknown demand. We prove that the production fluctuations can be interestingly smoothed and stabilized independent of the delivery frequency of the manufacturer used to satisfy the retailer’s demand, even if the retailer subsystem is unstable. The sufficient and necessary stability condition for the whole supply chain system is obtained. To further explore the production fluctuation problem, the bullwhip effect under unknown demand is explored based on a transfer function model with the purpose of disclosing the influences of parameters on production fluctuations. Finally, simulation experiments are used to validate the theoretical results with respect to inventory and production fluctuations.

The horizontal interaction between retailers, coupled with replenishment rules and time delays, makes the dynamics in supply chain systems highly complicated. This paper aims to explore the impacts of lateral transshipments on the stability, bullwhip effect, and other performance measurements in the context of a two-tiered supply chain system composed of one supplier and two retailers. In particular, we developed a unified discrete-time state space model to address two different scenarios of placing orders. Analytical stability results are derived, through which we found that inappropriate lateral transshipment policies readily destabilize the supply chain system. Moreover, the lead time of lateral transshipments further complicates the stability problem. Theoretical results are validated through simulation experiments and the influences of system parameters on performance measures are investigated numerically. Numerical simulations show that lateral transshipments help improve the customer service level for both retailers. It is also interesting to observe that the demand of the two retailers can be satisfied even if only one retailer places orders from the upstream supplier.

Acute myeloid leukemia (AML) is an acute leukemia common in most adults; its prevalence intensifies with age. The overall survival of AML is very poor because of therapeutic resistance. Azelaic acid (AZA) is non-toxic, non-teratogenic, and non-mutagenic and its antitumor effect on various tumor cells is well established; Nonetheless, its therapeutic effects in AML cells are largely unknown. In this study, it was shown that AZA significantly inhibits the cell viability and induces apoptosis in AML cells in a dose-dependent manner. Additionally, AZA suppressed the expression of phosphorylated Akt, Jab1 and Trx, and this suppression was enhanced by treatment with Jab1 siRNA. Furthermore, AZA sensitized AML cells to Ara-c chemotherapy. The suppressive effect of AZA on tumor growth was examined in vivo by subcutaneously inoculated AML cells in a tumor model using nude mice. These findings indicate that AZA is useful as an effective ingredient in antineoplastic activity.

Triple-negative breast cancer (TNBC) is an aggressive subgroup of breast cancer lack of effective target therapy. This study was to investigate the prognostic role of p53 and Ki-67 in 156 cases of TNBC patients. Logistic regression analysis was used to examine the association between clinical parameters and recurrence. Univariate and multivariate analyses were used to examine the association between clinical characteristics and disease-free survival (DFS) or overall survival (OS). Survival analyses using the Kaplan-Meier method were performed to examine the association between p53/Ki-67 and DFS and OS. Our data showed that p53 was positive in 71.3% and the Ki-67 high index was in 82.8% of TNBC. Elevated p53 and Ki-67 were associated with histological grade. The tumor size, lymph node involvement, and p53 expression are associated with risk of recurrence. Tumor size, lymph node involvement, family history, Ki-67 and p53 are independent variables associated with either DFS or OS. TNBC patients with positive p53 or Ki-67 high index or family history of cancer have a significant association with worse prognosis. This study suggests that p53, Ki-67 and family history are useful prognostic markers in TNBC.